教師資料查詢 | 類別: 會議論文 | 教師: 翁慶昌 Wong Ching-chang (瀏覽個人網頁)

標題:K-means-based fuzzy classifier design
學年88
學期2
發表日期2000/05/07
作品名稱K-means-based fuzzy classifier design
作品名稱(其他語言)
著者翁慶昌; Wong, Ching-chang; Chen, Chia-chong; Yeh, Shih-liang
作品所屬單位淡江大學電機工程學系
出版者Institute of Electrical and Electronics Engineers (IEEE)
會議名稱Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on
會議地點San Antonio, TX, USA
摘要In this paper, a method based on the K-means algorithm is proposed to efficiently design a fuzzy classifier so that the training patterns can be correctly classified by the proposed approach. In this method, the K-means algorithm is first used to partition the training data for each class into several clusters, and the cluster center and the radius for each cluster are calculated. Then, a fuzzy system design method that uses a fuzzy rule to represent a cluster is proposed such that a fuzzy classifier can be efficiently constructed to correctly classify the training data. The proposed method has the following features: 1) it does not need prior parameter definition; 2) it only needs a short training time; and 3) it is simple. Finally, two examples are used to illustrate and examine the proposed method for the fuzzy classifier design
關鍵字
語言英文
收錄於
會議性質國際
校內研討會地點
研討會時間20000507~20000507
通訊作者
國別美國
公開徵稿Y
出版型式紙本
出處Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on (Volume:1 ), pp.48-52
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